3-D machine vision systems utilize a number of different schemes such as range finding, structured light and binocular vision to see in three dimensions. Range finding and structured light schemes are typically the easiest to implement. Both techniques rely for depth cues on the way light or other radiation such as sound waves reflect from the surface of an object. Range finding systems typically time the reflection of the laser beam to the object and back again to measure its distance--similar to radar.
Different range finding sensors have been applied to scene analysis. These sensors may be classified into two types. One is based on the trigonometry of triangulation and the other is based on the time of flight. Triangulation range sensors are further classified into two types, one of which is based on a stereo pair of television cameras or one camera alternately positioned in two locations. The other type is based on the projection of a sheet of light by a scanning transmitter and recording the image of the reflected light by a television camera. Alternatively, the second type may emit light by a "rocking" receiver. The first type suffers from the problem of finding corresponding points in two images of the scene. Both types have two additional drawbacks. missing data for points seen by the transmitter but not by the receiver and vice versa, and poor accuracy for points that are distant from the sensors.
The above drawbacks are eliminated by utilizing the second type of range imaging sensor with a laser scanner. This type of range finding sensor is also classified into two schemes, one of which is based on the transmission of a laser pulse and measuring the arrival time of the reflected signal. The other scheme is based on transmitting an amplitude modulated laser beam and measuring the phase shift of the reflected signal.
Structured light systems project light in a controlled manner on the object. The system then determines the distance to the object by triangulation and deduces the object's shape from the pattern formed by the intersection of the object's surface with the beam of light. For example, planes of light falling on a convex surface will form a family of curves which form a chevron pattern on an angular object.
Binocular vision systems utilize two cameras and employ the same general approach as that used in human vision (i.e. binocular parallax). The slight disparity between the two views of the same scene is used as a depth cue, i.e. the greater the parallax the closer the object.
One problem associated with the development of a practical machine vision system based on binocular parallax is the "correspondence" problem. That is, objects in each view must match with one another before the disparity between the two views can be determined. Matching can be a problem because, as a result of the parallax, an object may appear slightly differently in the right and left views and may be partially or totally obscured in one view.
3-D vision systems which rely on the range finding or structured light schemes are also inherently limited because they require interaction with the object under observation. These systems may be adequate for many applications. However, a vision system should be passive to avoid putting constraints on the observed objects or their environment. The United States Patents to Stern et al U.S. Pat. No. 4,357,108 and DiMattio et al U.S. Pat. No. 4,335,962 both disclose method and apparatus for determining spatial information by applying radiant energy patterns to an object and thereafter recording the reflected radiant energy.
The U.S. Patent to Rossel et al U.S. Pat. No. 4,105,925 discloses an optical object locator which determines the position and orientation of an object on a conveyor. Two planes of light intersect at a single transverse line on the conveyor surface. The method assumes a constant viewing distance and perspective.
Special vision problems are encountered during vehicle assembly. For example, frequently during the assembly process a partially completed vehicle body proceeds down the assembly line while being loosely held by a carrying fixture. The exact position of the body is not known at any work station. Rather, the body is located within a finite window of uncertainty which is both known and constant. The window is generally so large that the automation of work at the station is either impossible or prohibitively expensive. Even with mechanical constraints designed to locate and hold the body, the positional uncertainty often precludes the use of automated tools.
A related problem is that of non-rigid bodies. In practice it has been observed that "identical" vehicle bodies produced on the same assembly line will often have unpredictable dimensional irregularities. These irregularities and the compliance of a partially completed body have come to be an accepted artifact of modern design and manufacturing practices. It is clear that future manufacturing systems must be able to gracefully tolerate these irregularities.
One possible solution to these problems is to design the entire assembly line to extremely high tolerances to ensure that the body locations in space are invariant from one body to the next. Also, it must be ensured that the bodies are indeed "identical". Such an approach is shown by the United States Patent to Fujii et al U.S. Pat. No. 4,458,628. The Fujii et al patent discloses an apparatus for applying adhesive to automobile windshield glass panels which includes a turntable assembly for supporting the glass panel and moving it so that the peripheral portion of the glass panel is continually exposed to an adhesive applying nozzle of an industrial robot. Such an approach however requires a relatively high initial investment and expensive retooling costs to hold different workpieces.
Other possible solution are disclosed in the United States Patents to U.S. Pat. Nos. Blanchard et al 3,618,742, Michaud et al 3,804,270, Birk et al 4,146,924, Pryor et al 4,373,804 and Masaki 4,380,696. Each of these patents discloses a machine vision system which provides visual data which is subsequently processed and put into a form utilized to alter the preprogrammed path of the robot so that the robot can perform work on the object.
Such prior art machine vision methods and systems, however, are inadequate to solve the compliance and irregularity problems of vehicle bodies in a factory environment.
One area of current interest in the automated "factory of the future" is the dispensing of an adhesive by a robot. New applications for adhesives and sealants are being introduced as automobile manufacturers aggressively pursue anti-corrosion programs. These materials are used in the assembly of such hem-flanged parts as doors, decks and hoods.
In some cases, sealing materials are used in conjunction with more conventional spot welding. A sealant is applied first and then the sheet metal is welded through the sealant. This combined approach allows the distance between spot welds to be increased while reducing the number of welds. Some manufacturers have eliminated welding altogether on some hem-flanged assemblies by employing structural adhesives.
A number of factors are leading manufacturers to adhesive bonding. For example, the need for fuel economy has motivated auto manufacturers to reduce weight by using lighter gauge metal. However, mechanical welds and thinner metal do no provide satisfactory structural strength.
Manual application of such adhesives and sealants however, are generally impractical because of the high throughput and high accuracy required. The automotive manufacturing environment also places exacting demands on systems that can automatically apply adhesives and sealants. When such adhesives and sealants are improperly applied incorrect bonding or squeeze-out occurs.
Application systems for such adhesives and sealants must easily adapt to current production lines of material handling systems. The work cell must be sized to accommodate even the largest automotive components. In addition, control systems must be compatible with factory communication systems. Finally, the systems must be able to compensate for such things as changes in workpiece geometry produced by tool and die wear, product redesign and manufacturing improvements.
In any assembly operation there are several points on the vehicle body called gauge holes which are relatively invariant and used as a baseline for all measurements. The foundation of a house and the keel of a ship are examples of other types of baselines. In vehicle assembly the entire structure of a body is assembled with respect to the carefully positioned guage holes. While the body as a whole may be somewhat non-rigid, the gauge holes maintain a constant relationship with respect to each other.